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ccf3a87e83
Introduces data-driven snapshot tests that regenerate capa freeze files for a curated set of samples in the tests/data submodule and compare the bytes against committed fixtures under tests/fixtures/freezes/. Any change that perturbs feature extraction surfaces as a test failure with a feature-count delta and a truncated unified diff.
257 lines
9.2 KiB
Python
257 lines
9.2 KiB
Python
# Copyright 2026 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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Data-driven feature snapshot tests.
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For every entry in `tests/fixtures/snapshots/features/manifest.json`, this
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module regenerates a capa freeze from the corresponding sample via
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`capa.features.freeze.main --reproducible`, compares it byte-for-byte
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against the committed `.frz` file, and on mismatch renders a unified diff
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of the freeze contents so a reviewer can see which features appeared,
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disappeared, or moved.
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A failing test means capa now extracts different features from the same
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sample than it used to. That can be intentional (you changed an extractor)
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or accidental (an unrelated change perturbed extraction); see the failure
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message for how to update the fixture or investigate.
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Refreshing a fixture after an intentional change::
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python -m capa.features.freeze --reproducible \\
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tests/data/<sample> tests/fixtures/snapshots/features/<name>.frz
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The manifest is edited by hand when samples are added or removed.
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"""
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from __future__ import annotations
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import json
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import zlib
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import difflib
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import tempfile
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from typing import Any, Optional
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from pathlib import Path
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import pytest
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from pydantic import BaseModel, ConfigDict
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import capa.features.freeze
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TESTS_DIR = Path(__file__).resolve().parent
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TESTS_DATA_DIR = TESTS_DIR / "data"
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FEATURE_SNAPSHOTS_DIR = TESTS_DATA_DIR / "fixtures" / "snapshots" / "features"
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MANIFEST_PATH = FEATURE_SNAPSHOTS_DIR / "manifest.json"
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class FeatureSnapshot(BaseModel):
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"""One entry in the feature snapshot manifest."""
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model_config = ConfigDict(frozen=True)
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name: str
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sample: str
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freeze: str
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explanation: str = ""
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# Git commit at which this fixture was last regenerated. Purely informational:
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# on test failure we surface it so a reviewer can run `git log <commit>..HEAD`
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# to see what's changed since. Not validated — humans keep it accurate.
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generated_at_commit: Optional[str] = None
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format: Optional[str] = None
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backend: Optional[str] = None
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os: Optional[str] = None
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@property
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def sample_path(self) -> Path:
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return TESTS_DATA_DIR / self.sample
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@property
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def freeze_path(self) -> Path:
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return FEATURE_SNAPSHOTS_DIR / self.freeze
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class Manifest(BaseModel):
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version: int = 1
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description: str = ""
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snapshots: list[FeatureSnapshot]
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@classmethod
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def from_file(cls, path: Path = MANIFEST_PATH) -> Manifest:
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return cls.model_validate_json(path.read_text(encoding="utf-8"))
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_SNAPSHOTS = Manifest.from_file().snapshots
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def _ids(snapshots: list[FeatureSnapshot]) -> list[str]:
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return [s.name for s in snapshots]
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def _regenerate(snapshot: FeatureSnapshot) -> bytes:
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"""Run the freeze CLI against the sample and return the produced bytes."""
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import logging
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root = logging.getLogger()
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handlers_before = list(root.handlers)
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with tempfile.TemporaryDirectory() as tmp:
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out_path = Path(tmp) / "out.frz"
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argv = [str(snapshot.sample_path), str(out_path), "--reproducible"]
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if snapshot.format is not None:
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argv += ["--format", snapshot.format]
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if snapshot.backend is not None:
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argv += ["--backend", snapshot.backend]
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if snapshot.os is not None:
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argv += ["--os", snapshot.os]
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rc = capa.features.freeze.main(argv)
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# capa.main.handle_common_args() unconditionally appends a RichHandler
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# to the root logger on every call. Since we call freeze.main() once per
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# snapshot, handlers accumulate and duplicate every log line. Remove
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# whatever was added so the next iteration starts clean.
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for h in root.handlers[:]:
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if h not in handlers_before:
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root.removeHandler(h)
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if rc != 0:
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raise RuntimeError(f"capa.features.freeze.main exited with status {rc}")
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return out_path.read_bytes()
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def _doc_to_lines(doc: dict[str, Any]) -> list[str]:
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"""
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Render a freeze JSON document to a list of lines suitable for unified-diffing.
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We pretty-print with sorted keys so that field reordering (which is
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meaningful for features) is preserved while key ordering within objects is
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normalized.
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"""
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return json.dumps(doc, indent=2, sort_keys=True).splitlines(keepends=True)
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def _load_freeze_doc(buf: bytes) -> dict[str, Any]:
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"""deserialize bytes to capa.features.freeze.Freeze, as JSON-like object.
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capa.features.freeze.loads() deserializes into a FeatureExtractor, not Freeze (or JSON, which we need for diffing).
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"""
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magic = capa.features.freeze.MAGIC
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assert buf[: len(magic)] == magic, "missing freeze magic header"
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return json.loads(zlib.decompress(buf[len(magic) :]).decode("utf-8"))
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def _format_mismatch(snapshot: FeatureSnapshot, expected: bytes, actual: bytes) -> str:
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"""Build a failure message describing how the freezes differ."""
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lines = [
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f"feature snapshot drift for {snapshot.name!r}:",
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f" sample: {snapshot.sample}",
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f" expected freeze: {snapshot.freeze_path}",
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" actual freeze: <regenerated>",
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f" expected size: {len(expected):,} bytes",
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f" actual size: {len(actual):,} bytes",
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]
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if snapshot.generated_at_commit:
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lines.append(f" last regenerated at: {snapshot.generated_at_commit}")
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expected_doc = _load_freeze_doc(expected)
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actual_doc = _load_freeze_doc(actual)
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expected_lines = _doc_to_lines(expected_doc)
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actual_lines = _doc_to_lines(actual_doc)
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# difflib.unified_diff uses SequenceMatcher which is O(n^2) for dissimilar
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# sequences. Large freeze documents (e.g. mimikatz) expand to millions of
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# JSON lines, making a naive diff take hours. Skip it when the input is too
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# large — the regeneration command below is the intended way to inspect.
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MAX_DIFFABLE_LINES = 100_000
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MAX_DIFF_LINES = 200
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total_lines = len(expected_lines) + len(actual_lines)
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lines.append("")
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if total_lines > MAX_DIFFABLE_LINES:
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lines.append(
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f"diff skipped: documents too large ({len(expected_lines):,} + {len(actual_lines):,} lines)."
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" Regenerate the fixture locally to inspect."
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)
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else:
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diff = list(
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difflib.unified_diff(
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expected_lines,
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actual_lines,
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fromfile=f"expected/{snapshot.freeze}",
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tofile=f"actual/{snapshot.freeze}",
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n=2,
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)
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)
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if len(diff) > MAX_DIFF_LINES:
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lines.append(f"unified diff ({len(diff)} lines, truncated to {MAX_DIFF_LINES}):")
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diff = diff[:MAX_DIFF_LINES]
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else:
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lines.append(f"unified diff ({len(diff)} lines):")
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lines.extend(line.rstrip("\n") for line in diff)
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lines.append("")
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lines.append("how and when to update this snapshot:")
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lines.append(" If this change to feature extraction is INTENTIONAL (you edited an extractor):")
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lines.append(" 1. regenerate the fixture:")
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lines.append(
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f" python -m capa.features.freeze --reproducible \\\n"
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f" {snapshot.sample_path} {snapshot.freeze_path}"
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)
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lines.append(
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" 2. update `generated_at_commit` in manifest.json to HEAD (the freeze CLI emits a suggested entry at INFO)."
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)
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lines.append(" If it is ACCIDENTAL (extraction shifted as a side effect of an unrelated change),")
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lines.append(" do NOT update the fixture; fix the root cause instead.")
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if snapshot.generated_at_commit:
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lines.append(
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f" To see what's changed since this fixture was last regenerated:\n"
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f" git log {snapshot.generated_at_commit}..HEAD -- capa/"
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)
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return "\n".join(lines)
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_BACKEND_AVAILABLE: dict[str, bool] = {}
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def _is_backend_available(backend: str) -> bool:
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if backend not in _BACKEND_AVAILABLE:
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if backend == "ida":
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try:
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import idapro # noqa: F401
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_BACKEND_AVAILABLE[backend] = True
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except ImportError:
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_BACKEND_AVAILABLE[backend] = False
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else:
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_BACKEND_AVAILABLE[backend] = True
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return _BACKEND_AVAILABLE[backend]
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@pytest.mark.parametrize("snapshot", _SNAPSHOTS, ids=_ids(_SNAPSHOTS))
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def test_feature_snapshot(snapshot: FeatureSnapshot):
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"""
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Regenerate the freeze for `snapshot.sample` and assert it matches
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`snapshot.freeze` byte-for-byte.
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"""
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if snapshot.backend and not _is_backend_available(snapshot.backend):
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pytest.skip(f"{snapshot.backend} backend not available")
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expected = snapshot.freeze_path.read_bytes()
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actual = _regenerate(snapshot)
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if actual == expected:
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return
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pytest.fail(_format_mismatch(snapshot, expected, actual))
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